Novel Methylation Patterns Predict Outcome in Uveal Melanoma

Total Page:16

File Type:pdf, Size:1020Kb

Novel Methylation Patterns Predict Outcome in Uveal Melanoma Article Novel Methylation Patterns Predict Outcome in Uveal Melanoma Sarah Tadhg Ferrier 1 and Julia Valdemarin Burnier 1,2,3,* 1 Cancer Research Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada, H4A 3J1; [email protected] 2 Experimental Pathology Unit, Department of Pathology, McGill University; Montreal, QC, Canada, H3A 0G4 3 Department of Oncology, McGill University; Montreal, QC, Canada, H3A 0G4 * Correspondence: [email protected] Table S1. Differentially methylated genes in the Pathways in Cancer KEGG pathway with a log FC ≥ 1.5. Average Average Log Fold Change Differentially Adjusted P Beta Beta ID Gene Name Species (High vs Low Methylated Probes Value Value, Value, Risk) Low High ABL proto-oncogene 1, non- ABL1 Homo sapiens cg13440206, −1.85238 1.39E−06 0.576589 0.259088 receptor tyrosine kinase(ABL1) cg02915920 −1.84042 8.03E−06 0.482846 0.192714 cg21195763 1.685721 3.13E−19 0.573548 0.83358 ADCY2 adenylate cyclase 2(ADCY2) Homo sapiens cg14116052 2.454448 4.3E−24 0.513149 0.885217 ADCY6 adenylate cyclase 6(ADCY6) Homo sapiens cg25196508 3.480923 2.9E−25 0.188362 0.792499 AKT serine/threonine kinase AKT1 Homo sapiens cg14116052 2.454448 4.3E−24 0.513149 0.885217 1(AKT1) bone morphogenetic protein BMP4 Homo sapiens cg08046044 1.527233 3.98E−06 0.049923 0.209543 4(BMP4) cg01873886 1.789942 2.55E−05 0.026254 0.1723 Life 2020, 10, x; doi: FOR PEER REVIEW www.mdpi.com/journal/life Life 2020, 10, x FOR PEER REVIEW 2 of 22 cyclin dependent kinase inhibitor CDKN1B Homo sapiens cg06197769 3.78761 1.9E−30 0.187364 0.82662 1B(CDKN1B) CTNNA3 catenin alpha 3(CTNNA3) Homo sapiens cg09538287 2.037243 5.62E−09 0.251955 0.539339 death associated protein kinase DAPK3 Homo sapiens cg22304239 1.939735 1.18E−13 3(DAPK3) endothelin receptor type EDNRB Homo sapiens cg18210860 2.815506 1.87E−14 0.444524 0.810551 B(EDNRB) cg24785726 3.163564 2.54E−15 0.080629 0.539854 cg23326536 3.195834 6.45E−17 0.071876 0.541248 cg13866767 3.463542 1.49E−19 0.28389 0.815008 endothelial PAS domain protein EPAS1 Homo sapiens cg21276379 1.824026 5.68E−14 0.186755 0.437118 1(EPAS1) cg17091312 2.112437 2.76E−23 ETS proto-oncogene 1, ETS1 Homo sapiens cg25244476 2.507626 9.92E−07 0.25583 0.602367 transcription factor(ETS1) FGF1 fibroblast growth factor 1(FGF1) Homo sapiens cg15371881 3.061708 4.38E−25 0.219393 0.69523 FZD6 frizzled class receptor 6(FZD6) Homo sapiens cg10929921 3.957203 3.22E−19 0.333365 0.912152 G protein subunit alpha GNA11 Homo sapiens cg02261780 2.268738 2.51E−16 0.353174 0.732472 11(GNA11) cg24366168 2.349167 6.69E−12 0.43427 0.894937 cg00168191 2.478771 1.2E−11 0.510916 0.876102 cg13527233 2.144414 1.19E−11 0.540858 0.863307 GNAI1 G protein subunit alpha i1(GNAI1) Homo sapiens cg05424060 1.904542 2.69E−07 GNB4 G protein subunit beta 4(GNB4) Homo sapiens cg01750654 1.647758 4.02E−11 0.594913 0.827501 cg03466124 1.862402 3.31E−08 0.108087 0.324521 Life 2020, 10, x FOR PEER REVIEW 3 of 22 G protein subunit gamma GNG11 Homo sapiens cg06439941 2.094159 1.67E−09 0.218242 0.565099 11(GNG11) cg08038054 2.335425 3.13E−11 0.069817 0.348166 cg02914800 3.14371 1.04E−14 0.10902 0.602134 glutathione S-transferase pi GSTP1 Homo sapiens cg22224704 2.261199 1.11E−08 0.19543 0.520111 1(GSTP1) cg11566244 3.087685 6.52E−12 0.134838 0.555003 insulin like growth factor 1 IGF1R Homo sapiens cg11852333 1.967845 3.57E−14 0.258781 0.568105 receptor(IGF1R) ITGA3 integrin subunit alpha 3(ITGA3) Homo sapiens cg12127162 1.833962 2.92E−16 0.254277 0.538208 ITGAV integrin subunit alpha V(ITGAV) Homo sapiens cg03192874 2.961775 2.21E−15 KRAS proto-oncogene, KRAS Homo sapiens cg23152216 2.293392 5.96E−27 0.470784 0.837552 GTPase(KRAS) lysophosphatidic acid receptor LPAR6 Homo sapiens cg03646329 2.221789 8.4E−09 0.105173 0.345011 6(LPAR6) mitogen-activated protein kinase MAPK8 Homo sapiens cg19612574 1.694113 4.14E−15 0.113088 0.332177 8(MAPK8) mitogen-activated protein kinase MAPK9 Homo sapiens cg09663237 2.203989 3.06E−06 0.584195 0.883176 9(MAPK9) MMP2 matrix metallopeptidase 2(MMP2) Homo sapiens cg00355286 1.518071 7.31E−10 0.183672 0.439098 platelet derived growth factor PDGFRA Homo sapiens cg02273436 1.911305 1.17E−06 0.160494 0.467324 receptor alpha(PDGFRA) phosphoinositide−3-kinase PIK3R1 Homo sapiens cg01251150 2.237358 1.26E−17 0.060815 0.28225 regulatory subunit 1(PIK3R1) Life 2020, 10, x FOR PEER REVIEW 4 of 22 pleckstrin homology and RhoGEF PLEKHG5 Homo sapiens cg07181374 1.727515 1.69E−17 domain containing G5(PLEKHG5) PML promyelocytic leukemia(PML) Homo sapiens cg01947066 1.959361 1.08E−06 peroxisome proliferator activated PPARD Homo sapiens cg26668919 2.934903 3.68E−17 receptor delta(PPARD) PRKCA protein kinase C alpha(PRKCA) Homo sapiens cg14121185 −2.67592 1.62E−20 0.874693 0.429846 cg05115424 1.608107 7.51E−10 0.081959 0.220044 cg09655520 1.820661 1.39E−09 0.166933 0.419827 phosphatase and tensin PTEN Homo sapiens cg26127345 1.535502 0.001508 0.429051 0.633389 homolog(PTEN) cg19358349 1.702888 0.000271 0.401807 0.644288 cg01228636 1.712449 0.000372 0.491384 0.734546 cg19634213 1.721931 0.00022 0.40649 0.663402 cg04616691 1.78722 0.000905 0.364272 0.561777 cg03236184 1.901193 7.83E−05 0.438936 0.706127 RARB retinoic acid receptor beta(RARB) Homo sapiens cg21902772 2.206659 9.56E−18 0.291665 0.708268 cg23518541 3.4762 1.05E−16 0.096579 0.60235 Ras association domain family RASSF1 Homo sapiens cg02930432 1.590468 2.75E−09 0.197452 0.462608 member 1(RASSF1) cg21418575 1.510304 9.39E−08 0.335072 0.572985 cg07130266 2.266083 3.24E−09 0.249514 0.57952 RB transcriptional corepressor RB1 Homo sapiens cg13221796 1.972518 2.27E−20 1(RB1) RXRB retinoid X receptor beta(RXRB) Homo sapiens cg07931652 1.523593 4.19E−17 0.524678 0.77896 Life 2020, 10, x FOR PEER REVIEW 5 of 22 solute carrier family 2 member SLC2A1 Homo sapiens cg22025263 2.001813 8.33E−11 0.510382 0.81735 1(SLC2A1) SMAD3 SMAD family member 3(SMAD3) Homo sapiens cg04809597 1.97252 1.92E−23 0.05713 0.252782 SUFU negative regulator of SUFU Homo sapiens cg09119776 1.824803 1.59E−16 0.068277 0.233147 hedgehog signaling(SUFU) transcription factor 7 like TCF7L1 Homo sapiens cg20693690 −1.5635 3.97E−07 0.533941 0.240248 1(TCF7L1) cg22834443 1.837207 1.9E−12 0.548775 0.843847 cg20693690 −1.5635 3.97E−07 0.533941 0.240248 transcription factor 7 like TCF7L2 Homo sapiens cg07168930 1.804367 1.5E−14 0.712649 0.911392 2(TCF7L2) cg03339956 2.395134 3.93E−26 0.218402 0.600015 transforming growth factor beta TGFB2 Homo sapiens cg11976166 −1.8673 2.93E−05 0.442588 0.167974 2(TGFB2) cg10484211 2.167142 1.63E−13 0.08019 0.33298 cg13285637 −1.8383 6.64E−05 0.424687 0.162007 cg06899755 −1.54824 0.000222 0.447125 0.173171 cg22021178 −1.50285 0.000406 0.359804 0.125219 Table S2. Differentially methylated genes in the Tumor Suppressors KEGG pathway with a log FC ≥ 1.5. Log Fold Change Average Average Differentially Adjusted P Gene Name Species (High vs Low Beta Value, Beta Value, Methylated Probes Value Risk) Low High Life 2020, 10, x FOR PEER REVIEW 6 of 22 ATM serine/threonine ATM Homo sapiens cg14761454 2.171709 5.33E−11 0.113337 0.410785 kinase(ATM) cyclin dependent kinase inhibitor CDKN1B Homo sapiens cg06197769 3.78761 1.9E−30 0.187364 0.82662 1B(CDKN1B) cyclin dependent kinase inhibitor CDKN1C Homo sapiens cg17265994 1.60087 5.24E−15 0.098808 0.272309 1C(CDKN1C) cg03143849 1.697443 4.88E−16 0.380944 0.710675 cyclin dependent kinase inhibitor CDKN2D Homo sapiens cg25685983 1.766552 7.18E−23 0.110149 0.323895 2D(CDKN2D) DAB2, clathrin adaptor DAB2 Homo sapiens cg12290311 3.117633 5.95E−21 0.09455 0.555251 protein(DAB2) death associated protein kinase DAPK3 Homo sapiens cg22304239 1.939735 1.18E−13 3(DAPK3) DIS3 like 3'−5' exoribonuclease DIS3L2 Homo sapiens cg14802771 2.279833 3.93E−17 0.193749 0.543178 2(DIS3L2) DLC1 Rho GTPase activating DLC1 Homo sapiens cg18792365 2.274905 5.82E−10 0.185786 0.565794 protein(DLC1) cg22045977 2.575186 2.44E−15 0.407574 0.828947 EFNA1 ephrin A1(EFNA1) Homo sapiens cg07207669 1.829389 7.93E−07 0.308278 0.606053 FES proto-oncogene, tyrosine FES Homo sapiens cg25647583 1.620561 1.83E−12 0.337424 0.613609 kinase(FES) cg26405020 1.775185 3.08E−16 0.103383 0.313802 cg09397246 1.7864 4.28E−11 0.038035 0.194971 hypoxia inducible factor 3 alpha HIF3A Homo sapiens cg12068280 2.287241 3.28E−19 0.23857 0.656095 subunit(HIF3A) Life 2020, 10, x FOR PEER REVIEW 7 of 22 hydroxyprostaglandin HPGD Homo sapiens cg03772063 2.169526 7.27E−13 0.544367 0.843968 dehydrogenase 15-(NAD)(HPGD) mutated in colorectal MCC Homo sapiens cg02528008 2.18208 3.41E−17 0.138006 0.447979 cancers(MCC) microtubule associated tumor MTUS1 Homo sapiens cg00121389 2.338386 4.67E−18 0.289024 0.711872 suppressor 1(MTUS1) cg01993952 3.183913 3.56E−18 0.331804 0.792952 cg23002008 3.231493 8.86E−18 0.394688 0.876206 cg12548824 3.485792 2.2E−25 0.250505 0.83362 cg18563140 3.558719 8.99E−23 PIN2/TERF1 interacting, PINX1 Homo sapiens cg26886855 2.717973 1.02E−10 telomerase inhibitor 1(PINX1) PML promyelocytic leukemia(PML) Homo sapiens cg01947066 1.959361 1.08E−06 PRKCD protein kinase C delta(PRKCD) Homo sapiens cg08170911 2.447478 8.68E−26 0.173984 0.533695 phosphatase and tensin PTEN Homo sapiens cg26127345 1.535502 0.001508 0.429051 0.633389 homolog(PTEN) cg19358349 1.702888 0.000271 0.401807 0.644288 cg01228636 1.712449 0.000372 0.491384 0.734546 cg19634213 1.721931 0.00022 0.40649 0.663402 cg04616691 1.78722 0.000905 0.364272 0.561777 cg03236184 1.901193 7.83E−05 0.438936 0.706127 Ras association domain family RASSF1 Homo sapiens cg02930432 1.590468 2.75E−09 0.197452 0.462608
Recommended publications
  • Endothelin System and Therapeutic Application of Endothelin Receptor
    xperim ACCESS Freely available online & E en OPEN l ta a l ic P in h l a C r m f o a c l a o n l o r g u y o J Journal of ISSN: 2161-1459 Clinical & Experimental Pharmacology Research Article Endothelin System and Therapeutic Application of Endothelin Receptor Antagonists Abebe Basazn Mekuria, Zemene Demelash Kifle*, Mohammedbrhan Abdelwuhab Department of Pharmacology, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia ABSTRACT Endothelin is a 21 amino acid molecule endogenous potent vasoconstrictor peptide. Endothelin is synthesized in vascular endothelial and smooth muscle cells, as well as in neural, renal, pulmonic, and inflammatory cells. It acts through a seven transmembrane endothelin receptor A (ETA) and endothelin receptor B (ETB) receptors belongs to G protein-coupled rhodopsin-type receptor superfamily. This peptide involved in pathogenesis of cardiovascular disorder like (heart failure, arterial hypertension, myocardial infraction and atherosclerosis), renal failure, pulmonary arterial hypertension and it also involved in pathogenesis of cancer. Potentially endothelin receptor antagonist helps the treatment of the above disorder. Currently, there are a lot of trails both per-clinical and clinical on endothelin antagonist for various cardiovascular, pulmonary and cancer disorder. Some are approved by FAD for the treatment. These agents are including both selective and non-selective endothelin receptor antagonist (ETA/B). Currently, Bosentan, Ambrisentan, and Macitentan approved
    [Show full text]
  • Outlier Kinase Expression by RNA Sequencing As Targets for Precision Therapy
    Published OnlineFirst February 5, 2013; DOI: 10.1158/2159-8290.CD-12-0336 RESEARCH ARTICLE Outlier Kinase Expression by RNA Sequencing as Targets for Precision Therapy Vishal Kothari 1 , Iris Wei 2 , Sunita Shankar 1 , 3 , Shanker Kalyana-Sundaram 1 , 3 , 8 , Lidong Wang 2 , Linda W. Ma 1 , Pankaj Vats 1 , Catherine S. Grasso 1 , Dan R. Robinson 1 , 3 , Yi-Mi Wu 1 , 3 , Xuhong Cao 7 , Diane M. Simeone 2 , 4 , 5 , Arul M. Chinnaiyan 1 , 3 , 4 , 6 , 7 , and Chandan Kumar-Sinha 1 , 3 ABSTRACT Protein kinases represent the most effective class of therapeutic targets in cancer; therefore, determination of kinase aberrations is a major focus of cancer genomic studies. Here, we analyzed transcriptome sequencing data from a compendium of 482 cancer and benign samples from 25 different tissue types, and defi ned distinct “outlier kinases” in individual breast and pancreatic cancer samples, based on highest levels of absolute and differential expression. Frequent outlier kinases in breast cancer included therapeutic targets like ERBB2 and FGFR4 , distinct from MET , AKT2 , and PLK2 in pancreatic cancer. Outlier kinases imparted sample-specifi c depend- encies in various cell lines, as tested by siRNA knockdown and/or pharmacologic inhibition. Outlier expression of polo-like kinases was observed in a subset of KRAS -dependent pancreatic cancer cell lines, and conferred increased sensitivity to the pan-PLK inhibitor BI-6727. Our results suggest that outlier kinases represent effective precision therapeutic targets that are readily identifi able through RNA sequencing of tumors. SIGNIFICANCE: Various breast and pancreatic cancer cell lines display sensitivity to knockdown or pharmacologic inhibition of sample-specifi c outlier kinases identifi ed by high-throughput transcrip- tome sequencing.
    [Show full text]
  • Lysophosphatidic Acid and Its Receptors: Pharmacology and Therapeutic Potential in Atherosclerosis and Vascular Disease
    JPT-107404; No of Pages 13 Pharmacology & Therapeutics xxx (2019) xxx Contents lists available at ScienceDirect Pharmacology & Therapeutics journal homepage: www.elsevier.com/locate/pharmthera Lysophosphatidic acid and its receptors: pharmacology and therapeutic potential in atherosclerosis and vascular disease Ying Zhou a, Peter J. Little a,b, Hang T. Ta a,c, Suowen Xu d, Danielle Kamato a,b,⁎ a School of Pharmacy, University of Queensland, Pharmacy Australia Centre of Excellence, Woolloongabba, QLD 4102, Australia b Department of Pharmacy, Xinhua College of Sun Yat-sen University, Tianhe District, Guangzhou 510520, China c Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, St Lucia, QLD 4072, Australia d Aab Cardiovascular Research Institute, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA article info abstract Available online xxxx Lysophosphatidic acid (LPA) is a collective name for a set of bioactive lipid species. Via six widely distributed G protein-coupled receptors (GPCRs), LPA elicits a plethora of biological responses, contributing to inflammation, Keywords: thrombosis and atherosclerosis. There have recently been considerable advances in GPCR signaling especially Lysophosphatidic acid recognition of the extended role for GPCR transactivation of tyrosine and serine/threonine kinase growth factor G-protein coupled receptors receptors. This review covers LPA signaling pathways in the light of new information. The use of transgenic and Atherosclerosis gene knockout animals, gene manipulated cells, pharmacological LPA receptor agonists and antagonists have Gproteins fi β-arrestins provided many insights into the biological signi cance of LPA and individual LPA receptors in the progression Transactivation of atherosclerosis and vascular diseases.
    [Show full text]
  • The Number of Genes
    Table S1. The numbers of KD genes in each KD time The number The number The number The number Cell lines of genes of genes of genes of genes (96h) (120h) (144h) PC3 3980 3822 128 1725 A549 3724 3724 0 0 MCF7 3688 3471 0 1837 HT29 3665 3665 0 0 A375 3826 3826 0 0 HA1E 3801 3801 0 0 VCAP 4134 34 4121 0 HCC515 3522 3522 0 0 Table S2. The predicted results in the PC3 cell line on the LINCS II data id target rank A07563059 ADRB2 48 A12896037 ADRA2C 91 A13021932 YES1 77 PPM1B;PPP1CC;PPP2CA; A13254067 584;1326;297;171;3335 PTPN1;PPP2R5A A16347691 GMNN 2219 PIK3CB;MTOR;PIK3CA;PIK A28467416 18;10;9;13;8 3CG;PIK3CD A28545468 EHMT2;MAOB 14;67 A29520968 HSPB1 1770 A48881734 EZH2 1596 A52922642 CACNA1C 201 A64553394 ADRB2 155 A65730376 DOT1L 3764 A82035391 JUN 378 A82156122 DPP4 771 HRH1;HTR2C;CHRM3;CH A82772293 2756;2354;2808;2367 RM1 A86248581 CDA 1785 A92800748 TEK 459 A93093700 LMNA 1399 K00152668 RARB 105 K01577834 ADORA2A 525 K01674964 HRH1;BLM 31;1314 K02314383 AR 132 K03194791 PDE4D 30 K03390685 MAP2K1 77 K06762493 GMNN;APEX1 1523;2360 K07106112 ERBB4;ERBB2;EGFR 497;60;23 K07310275 AKT1;MTOR;PIK3CA 13;12;1 K07753030 RGS4;BLM 3736;3080 K08109215 BRD2;BRD3;BRD4 1413;2786;3 K08248804 XIAP 88 K08586861 TBXA2R;MBNL1 297;3428 K08832567 GMNN;CA12 2544;50 LMNA;NFKB1;APEX1;EH K08976401 1322;341;3206;123 MT2 K09372874 IMPDH2 232 K09711437 PLA2G2A 59 K10859802 GPR119 214 K11267252 RET;ALK 395;760 K12609457 LMNA 907 K13094524 BRD4 7 K13662825 CDK4;CDK9;CDK5;CDK1 34;58;13;18 K14704277 LMNA;BLM 1697;1238 K14870255 AXL 1696 K15170068 MAN2B1 1756 K15179879
    [Show full text]
  • How Relevant Are Bone Marrow-Derived Mast Cells (Bmmcs) As Models for Tissue Mast Cells? a Comparative Transcriptome Analysis of Bmmcs and Peritoneal Mast Cells
    cells Article How Relevant Are Bone Marrow-Derived Mast Cells (BMMCs) as Models for Tissue Mast Cells? A Comparative Transcriptome Analysis of BMMCs and Peritoneal Mast Cells 1, 2, 1 1 2,3 Srinivas Akula y , Aida Paivandy y, Zhirong Fu , Michael Thorpe , Gunnar Pejler and Lars Hellman 1,* 1 Department of Cell and Molecular Biology, Uppsala University, The Biomedical Center, Box 596, SE-751 24 Uppsala, Sweden; [email protected] (S.A.); [email protected] (Z.F.); [email protected] (M.T.) 2 Department of Medical Biochemistry and Microbiology, Uppsala University, The Biomedical Center, Box 589, SE-751 23 Uppsala, Sweden; [email protected] (A.P.); [email protected] (G.P.) 3 Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Box 7011, SE-75007 Uppsala, Sweden * Correspondence: [email protected]; Tel.: +46-(0)18-471-4532; Fax: +46-(0)18-471-4862 These authors contributed equally to this work. y Received: 29 July 2020; Accepted: 16 September 2020; Published: 17 September 2020 Abstract: Bone marrow-derived mast cells (BMMCs) are often used as a model system for studies of the role of MCs in health and disease. These cells are relatively easy to obtain from total bone marrow cells by culturing under the influence of IL-3 or stem cell factor (SCF). After 3 to 4 weeks in culture, a nearly homogenous cell population of toluidine blue-positive cells are often obtained. However, the question is how relevant equivalents these cells are to normal tissue MCs. By comparing the total transcriptome of purified peritoneal MCs with BMMCs, here we obtained a comparative view of these cells.
    [Show full text]
  • G Protein-Coupled Receptors
    G PROTEIN-COUPLED RECEPTORS Overview:- The completion of the Human Genome Project allowed the identification of a large family of proteins with a common motif of seven groups of 20-24 hydrophobic amino acids arranged as α-helices. Approximately 800 of these seven transmembrane (7TM) receptors have been identified of which over 300 are non-olfactory receptors (see Frederikson et al., 2003; Lagerstrom and Schioth, 2008). Subdivision on the basis of sequence homology allows the definition of rhodopsin, secretin, adhesion, glutamate and Frizzled receptor families. NC-IUPHAR recognizes Classes A, B, and C, which equate to the rhodopsin, secretin, and glutamate receptor families. The nomenclature of 7TM receptors is commonly used interchangeably with G protein-coupled receptors (GPCR), although the former nomenclature recognises signalling of 7TM receptors through pathways not involving G proteins. For example, adiponectin and membrane progestin receptors have some sequence homology to 7TM receptors but signal independently of G-proteins and appear to reside in membranes in an inverted fashion compared to conventional GPCR. Additionally, the NPR-C natriuretic peptide receptor has a single transmembrane domain structure, but appears to couple to G proteins to generate cellular responses. The 300+ non-olfactory GPCR are the targets for the majority of drugs in clinical usage (Overington et al., 2006), although only a minority of these receptors are exploited therapeutically. Signalling through GPCR is enacted by the activation of heterotrimeric GTP-binding proteins (G proteins), made up of α, β and γ subunits, where the α and βγ subunits are responsible for signalling. The α subunit (tabulated below) allows definition of one series of signalling cascades and allows grouping of GPCRs to suggest common cellular, tissue and behavioural responses.
    [Show full text]
  • Anti-GNB4 (GW21993)
    3050 Spruce Street, Saint Louis, MO 63103 USA Tel: (800) 521-8956 (314) 771-5765 Fax: (800) 325-5052 (314) 771-5757 email: [email protected] Product Information Anti-GNB4 antibody produced in chicken, affinity isolated antibody Catalog Number GW21993 Formerly listed as GenWay Catalog Number 15-288-21993, Guanine nucleotide-binding protein subunit beta 4 Anti- body. The product is a clear, colorless solution in phosphate – Storage Temperature Store at 20 °C buffered saline, pH 7.2, containing 0.02% sodium azide. Synonyms: Guanine nucleotide-binding protein, beta-4 Species Reactivity: Human, mouse subunit, Transducin beta chain 4 Tested Applications: WB Product Description Recommended Dilutions: Recommended starting dilution Guanine nucleotide-binding proteins (G proteins) are for Western blot analysis is 1:500, for tissue or cell staining involved as a modulator or transducer in various trans- 1:200. membrane signaling systems. The beta and gamma chains are required for the GTPase activity. for replacement of GDP Note: Optimal concentrations and conditions for each by GTP. and for G protein-effector interaction. application should be determined by the user. NCBI Accession number: NP_067642.1 Precautions and Disclaimer Swiss Prot Accession number: Q9HAV0 This product is for R&D use only, not for drug, household, or other uses. Due to the sodium azide content a material Gene Information: Human .. GNB4 (59345) safety data sheet (MSDS) for this product has been sent to Immunogen: Recombinant protein Guanine nucleotide- the attention of the safety officer of your institution. Please binding protein, beta-4 subunit consult the Material Safety Data Sheet for information regarding hazards and safe handling practices.
    [Show full text]
  • Involvement of the Sigma-1 Receptor in Methamphetamine-Mediated Changes to Astrocyte Structure and Function" (2020)
    University of Kentucky UKnowledge Theses and Dissertations--Medical Sciences Medical Sciences 2020 Involvement of the Sigma-1 Receptor in Methamphetamine- Mediated Changes to Astrocyte Structure and Function Richik Neogi University of Kentucky, [email protected] Author ORCID Identifier: https://orcid.org/0000-0002-8716-8812 Digital Object Identifier: https://doi.org/10.13023/etd.2020.363 Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Neogi, Richik, "Involvement of the Sigma-1 Receptor in Methamphetamine-Mediated Changes to Astrocyte Structure and Function" (2020). Theses and Dissertations--Medical Sciences. 12. https://uknowledge.uky.edu/medsci_etds/12 This Master's Thesis is brought to you for free and open access by the Medical Sciences at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Medical Sciences by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT: I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained needed written permission statement(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine) which will be submitted to UKnowledge as Additional File. I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and royalty-free license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known.
    [Show full text]
  • Multi-Functionality of Proteins Involved in GPCR and G Protein Signaling: Making Sense of Structure–Function Continuum with In
    Cellular and Molecular Life Sciences (2019) 76:4461–4492 https://doi.org/10.1007/s00018-019-03276-1 Cellular andMolecular Life Sciences REVIEW Multi‑functionality of proteins involved in GPCR and G protein signaling: making sense of structure–function continuum with intrinsic disorder‑based proteoforms Alexander V. Fonin1 · April L. Darling2 · Irina M. Kuznetsova1 · Konstantin K. Turoverov1,3 · Vladimir N. Uversky2,4 Received: 5 August 2019 / Revised: 5 August 2019 / Accepted: 12 August 2019 / Published online: 19 August 2019 © Springer Nature Switzerland AG 2019 Abstract GPCR–G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signal- ing cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand–GPCR and GPCR–G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defnes an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR–G protein system represents an illustrative example of the protein structure–function continuum, where structures of the involved proteins represent a complex mosaic of diferently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fne-tuned by various post-translational modifcations and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specifc partners.
    [Show full text]
  • Association of Single Nucleotide Polymorphisms of Endothelin
    Association of Single Nucleotide Polymorphisms of Endothelin, Orexin and Vascular Endothelial Growth Factor Receptor Genes with Obstructive Sleep Apnea among Thai Ethnic Kankanit Rattanathanawan PhD*, Panaree Busarakumtragul PhD**, Polphet Thongket MSc****, Chairat Neruntarat MD***, Wasana Sukhumsirichart PhD**** * Innovative Learning Center, Srinakharinwirot University, Bangkok, Thailand ** Department of Physiology, Faculty of Medicine, Srinakharinwirot University, Bangkok, Thailand *** Department of Otolaryngology, Faculty of Medicine, Srinakharinwirot University, Nakhon Nayok, Thailand **** Department of Biochemistry, Faculty of Medicine, Srinakharinwirot University, Bangkok, Thailand Background: Obstructive sleep apnea (OSA) is a complex disorder characterized by repetitive collapse of upper airway during sleep which strongly influenced by genetic factors, especially those affect regulation of the sleep-wake cycle and endothelial function. Objective: This study investigated the association between single nucleotide polymorphisms (SNPs) in endothelin (EDNRA), orexin (OX1R, OX2R) and vascular endothelial growth factor (VEGFR1) receptor genes with risk of OSA in Thai population. Material and Method: All subjects were diagnosed by overnight polysomnography (PSG) before divided into OSA (59) and NOSA (60) groups based on their apnea-hypopnea index (AHI). Serum lipid levels were examined by using enzymatic colorimetric and homogeneous methods. DNAs were extracted and genotyped the SNPs by polymerase chain reaction (PCR) and high-resolution
    [Show full text]
  • Convergent Molecular, Cellular, and Cortical Neuroimaging Signatures of Major Depressive Disorder
    Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder Kevin M. Andersona,1, Meghan A. Collinsa, Ru Kongb,c,d,e,f, Kacey Fanga, Jingwei Lib,c,d,e,f, Tong Heb,c,d,e,f, Adam M. Chekroudg,h, B. T. Thomas Yeob,c,d,e,f,i, and Avram J. Holmesa,g,j aDepartment of Psychology, Yale University, New Haven, CT 06520; bDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore; cCentre for Sleep and Cognition, National University of Singapore, Singapore; dClinical Imaging Research Centre, National University of Singapore, Singapore; eN.1 Institute for Health, National University of Singapore, Singapore; fInstitute for Digital Medicine, National University of Singapore, Singapore; gDepartment of Psychiatry, Yale University, New Haven, CT 06520; hSpring Health, New York, NY 10001; iGraduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore; and jDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 Edited by Huda Akil, University of Michigan, Ann Arbor, MI, and approved August 12, 2020 (received for review May 5, 2020) Major depressive disorder emerges from the complex interactions detail. To date, there have been few opportunities to directly of biological systems that span genes and molecules through cells, explore the depressive phenotype across levels of analysis—from networks, and behavior. Establishing how neurobiological pro- genes and molecules through cells, circuits, networks, and cesses coalesce to contribute to depression requires a multiscale behavior—simultaneously (14). approach, encompassing measures of brain structure and function In vivo neuroimaging has identified depression-related corre- as well as genetic and cell-specific transcriptional data.
    [Show full text]
  • Peripheral Regulation of Pain and Itch
    Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1596 Peripheral Regulation of Pain and Itch ELÍN INGIBJÖRG MAGNÚSDÓTTIR ACTA UNIVERSITATIS UPSALIENSIS ISSN 1651-6206 ISBN 978-91-513-0746-6 UPPSALA urn:nbn:se:uu:diva-392709 2019 Dissertation presented at Uppsala University to be publicly examined in A1:107a, BMC, Husargatan 3, Uppsala, Friday, 25 October 2019 at 13:00 for the degree of Doctor of Philosophy (Faculty of Medicine). The examination will be conducted in English. Faculty examiner: Professor emeritus George H. Caughey (University of California, San Francisco). Abstract Magnúsdóttir, E. I. 2019. Peripheral Regulation of Pain and Itch. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1596. 71 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0746-6. Pain and itch are diverse sensory modalities, transmitted by the somatosensory nervous system. Stimuli such as heat, cold, mechanical pain and itch can be transmitted by different neuronal populations, which show considerable overlap with regards to sensory activation. Moreover, the immune and nervous systems can be involved in extensive crosstalk in the periphery when reacting to these stimuli. With recent advances in genetic engineering, we now have the possibility to study the contribution of distinct neuron types, neurotransmitters and other mediators in vivo by using gene knock-out mice. The neuropeptide calcitonin gene-related peptide (CGRP) and the ion channel transient receptor potential cation channel subfamily V member 1 (TRPV1) have both been implicated in pain and itch transmission. In Paper I, the Cre- LoxP system was used to specifically remove CGRPα from the primary afferent population that expresses TRPV1.
    [Show full text]